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DBMS > Amazon Redshift vs. Apache Drill vs. Apache Impala vs. Spark SQL

System Properties Comparison Amazon Redshift vs. Apache Drill vs. Apache Impala vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Drill  Xexclude from comparisonApache Impala  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageAnalytic DBMS for HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftdrill.apache.orgimpala.apache.orgspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftdrill.apache.org/­docsimpala.apache.org/­impala-docs.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)Apache Software FoundationApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation
Initial release2012201220132014
Current release1.20.3, January 20234.1.0, June 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Scala
Server operating systemshostedLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesrestrictednoyesno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL SELECT statement is SQL:2003 compliantSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++All languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functionsyes infouser defined functions and integration of map-reduceno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesDepending on the underlying data sourceyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesDepending on the underlying data sourcenono
User concepts infoAccess controlfine grained access rights according to SQL-standardDepending on the underlying data sourceAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno

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More resources
Amazon RedshiftApache DrillApache ImpalaSpark SQL
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